A Cooperative Agent-Based Multiple Neighborhood Search for the Capacitated Vehicle Routing Problem

Abstract

The chapter proposes a new hybrid approach for solving Capacitated Vehicle Routing Problem (CVRP), which integrates the cooperative multiple neighborhood search with a multi-agent paradigm. Using the multiple neighborhoods, explored by different heuristics during the search allows one to guide the search and avoid the reaching unsatisfactory results, whenever the search is getting trapped in a local optimum. On the other hand, a multi-agent architecture provides an effective mechanism for solving the problem in parallel and assures cooperation between agents (representing search methods) operating on a sharable population of solutions. Different strategies of exploration of multiple neighborhoods have been considered in the chapter. Some of them search for the best solutions using a family of still deeper neighborhoods, while others use the idea of systematically changing different neighborhoods according to the predefined order (neighborhoods were explored in randomly order or the order of exploration of neighborhoods were based on the neighborhood size). In order to validate the proposed approach a computational experiment has been carried out. It confirmed that using multiple neighborhoods may improve the computational results comparing to the cases, when only one neighborhood is explored during the search.